Pandas Profiling Report

Dataset statistics

Number of variables	18
Number of observations	10496
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.4 MiB
Average record size in memory	136.0 B

Variable types

Numeric	11
Boolean	3
Categorical	4

Alerts

`df_index` is highly correlated with `UserID` and 1 other fields	High correlation
`UserID` is highly correlated with `df_index` and 1 other fields	High correlation
`Yearly_avg_view_on_travel_page` is highly correlated with `Daily_Avg_mins_spend_on_traveling_page`	High correlation
`total_likes_on_outofstation_checkin_received` is highly correlated with `Daily_Avg_mins_spend_on_traveling_page`	High correlation
`montly_avg_comment_on_company_page` is highly correlated with `df_index` and 1 other fields	High correlation
`Daily_Avg_mins_spend_on_traveling_page` is highly correlated with `Yearly_avg_view_on_travel_page` and 1 other fields	High correlation
`df_index` is highly correlated with `UserID` and 1 other fields	High correlation
`UserID` is highly correlated with `df_index` and 1 other fields	High correlation
`Yearly_avg_view_on_travel_page` is highly correlated with `total_likes_on_outofstation_checkin_received` and 1 other fields	High correlation
`total_likes_on_outofstation_checkin_received` is highly correlated with `Yearly_avg_view_on_travel_page` and 1 other fields	High correlation
`montly_avg_comment_on_company_page` is highly correlated with `df_index` and 1 other fields	High correlation
`Daily_Avg_mins_spend_on_traveling_page` is highly correlated with `Yearly_avg_view_on_travel_page` and 1 other fields	High correlation
`df_index` is highly correlated with `UserID`	High correlation
`UserID` is highly correlated with `df_index`	High correlation
`df_index` is highly correlated with `UserID` and 2 other fields	High correlation
`UserID` is highly correlated with `df_index` and 2 other fields	High correlation
`Yearly_avg_view_on_travel_page` is highly correlated with `total_likes_on_outofstation_checkin_received` and 1 other fields	High correlation
`preferred_location_type` is highly correlated with `df_index` and 1 other fields	High correlation
`total_likes_on_outofstation_checkin_received` is highly correlated with `Yearly_avg_view_on_travel_page` and 1 other fields	High correlation
`montly_avg_comment_on_company_page` is highly correlated with `df_index` and 2 other fields	High correlation
`working_flag` is highly correlated with `montly_avg_comment_on_company_page`	High correlation
`Daily_Avg_mins_spend_on_traveling_page` is highly correlated with `Yearly_avg_view_on_travel_page` and 1 other fields	High correlation
`df_index` has unique values	Unique
`UserID` has unique values	Unique
`week_since_last_outstation_checkin` has 917 (8.7%) zeros	Zeros

Reproduction

Analysis started	2022-05-01 03:47:49.202366
Analysis finished	2022-05-01 03:48:15.421813
Duration	26.22 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10496
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6265.490949

Minimum	0
Maximum	11759
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	0
5-th percentile	706.75
Q1	3435.75
median	6511.5
Q3	9135.25
95-th percentile	11234.25
Maximum	11759
Range	11759
Interquartile range (IQR)	5699.5

Descriptive statistics

Standard deviation	3345.361909
Coefficient of variation (CV)	0.533934521
Kurtosis	-1.138692635
Mean	6265.490949
Median Absolute Deviation (MAD)	2822
Skewness	-0.1580828039
Sum	65762593
Variance	11191446.3
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
757	1	< 0.1%
4855	1	< 0.1%
11000	1	< 0.1%
8953	1	< 0.1%
2812	1	< 0.1%
765	1	< 0.1%
6910	1	< 0.1%
4863	1	< 0.1%
11008	1	< 0.1%
Other values (10486)	10486	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
8	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%
12	1	< 0.1%

Value	Count	Frequency (%)
11759	1	< 0.1%
11758	1	< 0.1%
11757	1	< 0.1%
11756	1	< 0.1%
11755	1	< 0.1%
11754	1	< 0.1%
11753	1	< 0.1%
11752	1	< 0.1%
11751	1	< 0.1%
11750	1	< 0.1%

UserID
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10496
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1006266.491

Minimum	1000001
Maximum	1011760
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	1000001
5-th percentile	1000707.75
Q1	1003436.75
median	1006512.5
Q3	1009136.25
95-th percentile	1011235.25
Maximum	1011760
Range	11759
Interquartile range (IQR)	5699.5

Descriptive statistics

Standard deviation	3345.361909
Coefficient of variation (CV)	0.003324528779
Kurtosis	-1.138692635
Mean	1006266.491
Median Absolute Deviation (MAD)	2822
Skewness	-0.1580828039
Sum	1.056177309 × 10¹⁰
Variance	11191446.3
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1003172	1	< 0.1%
1008288	1	< 0.1%
1006010	1	< 0.1%
1009029	1	< 0.1%
1011291	1	< 0.1%
1011608	1	< 0.1%
1008980	1	< 0.1%
1005192	1	< 0.1%
1007441	1	< 0.1%
1002936	1	< 0.1%
Other values (10486)	10486	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1000001	1	< 0.1%
1000002	1	< 0.1%
1000003	1	< 0.1%
1000004	1	< 0.1%
1000005	1	< 0.1%
1000006	1	< 0.1%
1000009	1	< 0.1%
1000011	1	< 0.1%
1000012	1	< 0.1%
1000013	1	< 0.1%

Value	Count	Frequency (%)
1011760	1	< 0.1%
1011759	1	< 0.1%
1011758	1	< 0.1%
1011757	1	< 0.1%
1011756	1	< 0.1%
1011755	1	< 0.1%
1011754	1	< 0.1%
1011753	1	< 0.1%
1011752	1	< 0.1%
1011751	1	< 0.1%

Buy_ticket
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	10.4 KiB

False	8794
True	1702

Common Values
Chart

Value	Count	Frequency (%)
False	8794	83.8%
True	1702	16.2%

Yearly_avg_view_on_travel_page
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	330
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	281.2844893

Minimum	92.5
Maximum	464
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	92.5
5-th percentile	182
Q1	232
median	271
Q3	325
95-th percentile	410
Maximum	464
Range	371.5
Interquartile range (IQR)	93

Descriptive statistics

Standard deviation	68.15326205
Coefficient of variation (CV)	0.2422929974
Kurtosis	-0.3657891531
Mean	281.2844893
Median Absolute Deviation (MAD)	45
Skewness	0.4270026329
Sum	2952362
Variance	4644.867129
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
255	169	1.6%
262	163	1.6%
270	160	1.5%
232	137	1.3%
217	137	1.3%
247	123	1.2%
240	120	1.1%
225	118	1.1%
285	117	1.1%
264	116	1.1%
Other values (320)	9136	87.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
92.5	8	0.1%
135	3	< 0.1%
136	8	0.1%
137	6	0.1%
138	3	< 0.1%
140	2	< 0.1%
141	3	< 0.1%
142	4	< 0.1%
143	7	0.1%
144	19	0.2%

Value	Count	Frequency (%)
464	1	< 0.1%
463	1	< 0.1%
462	2	< 0.1%
461	2	< 0.1%
460	3	< 0.1%
459	2	< 0.1%
458	1	< 0.1%
457	3	< 0.1%
456	5	< 0.1%
455	7	0.1%

preferred_device
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	82.1 KiB

Mobile	9388
Laptop	1108

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mobile
2nd row	Mobile
3rd row	Mobile
4th row	Mobile
5th row	Mobile

Common Values

Value	Count	Frequency (%)
Mobile	9388	89.4%
Laptop	1108	10.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
mobile	9388	89.4%
laptop	1108	10.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

total_likes_on_outstation_checkin_given
Real number (ℝ_≥0)

Distinct	7565
Distinct (%)	72.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	28155.04268

Minimum	3570
Maximum	76841
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	3570
5-th percentile	5748
Q1	16321
median	28178
Q3	40529.25
95-th percentile	49881.5
Maximum	76841
Range	73271
Interquartile range (IQR)	24208.25

Descriptive statistics

Standard deviation	14119.85805
Coefficient of variation (CV)	0.5015036989
Kurtosis	-1.180383428
Mean	28155.04268
Median Absolute Deviation (MAD)	12009
Skewness	-0.005701374773
Sum	295515328
Variance	199370391.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11515	11	0.1%
18550	9	0.1%
37870	9	0.1%
24185	9	0.1%
40110	8	0.1%
44905	8	0.1%
51415	7	0.1%
20125	7	0.1%
31325	7	0.1%
40495	7	0.1%
Other values (7555)	10414	99.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3570	2	< 0.1%
3577	1	< 0.1%
3578	1	< 0.1%
3605	2	< 0.1%
3611	1	< 0.1%
3614	1	< 0.1%
3618	1	< 0.1%
3620	1	< 0.1%
3621	1	< 0.1%
3631	1	< 0.1%

Value	Count	Frequency (%)
76841	2	< 0.1%
52512	1	< 0.1%
52509	1	< 0.1%
52498	1	< 0.1%
52495	1	< 0.1%
52487	1	< 0.1%
52479	1	< 0.1%
52474	1	< 0.1%
52469	1	< 0.1%
52465	1	< 0.1%

yearly_avg_Outstation_checkins
Real number (ℝ_≥0)

Distinct	29
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.282869665

Minimum	1
Maximum	29
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	41.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	5
Q3	14
95-th percentile	26
Maximum	29
Range	28
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	8.567258547
Coefficient of variation (CV)	1.034334584
Kurtosis	-0.3412692429
Mean	8.282869665
Median Absolute Deviation (MAD)	4
Skewness	0.9699234679
Sum	86937
Variance	73.39791901
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
1	3794	36.1%
2	844	8.0%
10	617	5.9%
9	340	3.2%
7	336	3.2%
3	336	3.2%
8	320	3.0%
5	261	2.5%
4	256	2.4%
6	236	2.2%
Other values (19)	3156	30.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	3794	36.1%
2	844	8.0%
3	336	3.2%
4	256	2.4%
5	261	2.5%
6	236	2.2%
7	336	3.2%
8	320	3.0%
9	340	3.2%
10	617	5.9%

Value	Count	Frequency (%)
29	184	1.8%
28	160	1.5%
27	89	0.8%
26	172	1.6%
25	172	1.6%
24	201	1.9%
23	189	1.8%
22	133	1.3%
21	133	1.3%
20	172	1.6%

member_in_family
Real number (ℝ_≥0)

Distinct	6
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.924828506

Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	41.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	4
95-th percentile	4
Maximum	10
Range	9
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.042118709
Coefficient of variation (CV)	0.3563007907
Kurtosis	1.278422445
Mean	2.924828506
Median Absolute Deviation (MAD)	1
Skewness	-0.00321649857
Sum	30699
Variance	1.086011405
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
3	4109	39.1%
4	2858	27.2%
2	1989	19.0%
1	1197	11.4%
5	333	3.2%
10	10	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1197	11.4%
2	1989	19.0%
3	4109	39.1%
4	2858	27.2%
5	333	3.2%
10	10	0.1%

Value	Count	Frequency (%)
10	10	0.1%
5	333	3.2%
4	2858	27.2%
3	4109	39.1%
2	1989	19.0%
1	1197	11.4%

preferred_location_type
Categorical

HIGH CORRELATION

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	82.1 KiB

Beach	2424
Financial	1893
Historical site	1856
Medical	1463
Other	1307
Other values (2)	1553

Length

Max length	15
Median length	8
Mean length	8.649199695
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Financial
2nd row	Financial
3rd row	Other
4th row	Financial
5th row	Medical

Common Values

Value	Count	Frequency (%)
Beach	2424	23.1%
Financial	1893	18.0%
Historical site	1856	17.7%
Medical	1463	13.9%
Other	1307	12.5%
Entertainment	917	8.7%
Trekking	636	6.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
beach	2424	19.6%
financial	1893	15.3%
historical	1856	15.0%
site	1856	15.0%
medical	1463	11.8%
other	1307	10.6%
entertainment	917	7.4%
trekking	636	5.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Yearly_avg_comment_on_travel_page
Real number (ℝ_≥0)

Distinct	97
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	75.02238948

Minimum	3
Maximum	147
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	3
5-th percentile	41
Q1	57
median	75
Q3	93
95-th percentile	109
Maximum	147
Range	144
Interquartile range (IQR)	36

Descriptive statistics

Standard deviation	21.78264525
Coefficient of variation (CV)	0.2903485932
Kurtosis	-0.7375029978
Mean	75.02238948
Median Absolute Deviation (MAD)	18
Skewness	-0.07411929514
Sum	787435
Variance	474.483634
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
96	175	1.7%
90	173	1.6%
66	171	1.6%
56	169	1.6%
72	167	1.6%
80	166	1.6%
60	163	1.6%
91	161	1.5%
87	160	1.5%
61	159	1.5%
Other values (87)	8832	84.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3	29	0.3%
31	24	0.2%
32	43	0.4%
33	34	0.3%
34	35	0.3%
35	39	0.4%
36	49	0.5%
37	44	0.4%
38	60	0.6%
39	57	0.5%

Value	Count	Frequency (%)
147	3	< 0.1%
125	7	0.1%
124	3	< 0.1%
123	8	0.1%
122	10	0.1%
121	11	0.1%
120	10	0.1%
119	24	0.2%
118	24	0.2%
117	25	0.2%

total_likes_on_outofstation_checkin_received
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5323
Distinct (%)	50.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6393.061928

Minimum	1009
Maximum	16574.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	1009
5-th percentile	2136
Q1	2948.5
median	4948
Q3	8398.25
95-th percentile	16574.5
Maximum	16574.5
Range	15565.5
Interquartile range (IQR)	5449.75

Descriptive statistics

Standard deviation	4344.08664
Coefficient of variation (CV)	0.6795001658
Kurtosis	0.2920306832
Mean	6393.061928
Median Absolute Deviation (MAD)	2192
Skewness	1.164642767
Sum	67101578
Variance	18871088.74
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
16574.5	822	7.8%
2377	11	0.1%
2404	9	0.1%
2342	9	0.1%
2437	9	0.1%
2387	8	0.1%
2380	8	0.1%
2570	8	0.1%
2096	8	0.1%
2793	8	0.1%
Other values (5313)	9596	91.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1009	2	< 0.1%
1014	1	< 0.1%
1017	1	< 0.1%
1050	1	< 0.1%
1051	1	< 0.1%
1052	2	< 0.1%
1055	1	< 0.1%
1058	1	< 0.1%
1060	1	< 0.1%
1061	2	< 0.1%

Value	Count	Frequency (%)
16574.5	822	7.8%
16567	1	< 0.1%
16561	1	< 0.1%
16505	1	< 0.1%
16495	1	< 0.1%
16491	1	< 0.1%
16487	1	< 0.1%
16481	1	< 0.1%
16480	1	< 0.1%
16477	1	< 0.1%

week_since_last_outstation_checkin
Real number (ℝ_≥0)

ZEROS

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.20788872

Minimum	0
Maximum	11
Zeros	917
Zeros (%)	8.7%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	3
Q3	5
95-th percentile	9
Maximum	11
Range	11
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.614220407
Coefficient of variation (CV)	0.8149348796
Kurtosis	-0.04186660285
Mean	3.20788872
Median Absolute Deviation (MAD)	2
Skewness	0.9118567761
Sum	33670
Variance	6.834148339
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
1	2733	26.0%
3	1605	15.3%
2	1502	14.3%
4	993	9.5%
0	917	8.7%
5	643	6.1%
6	585	5.6%
7	545	5.2%
9	410	3.9%
8	384	3.7%
Other values (2)	179	1.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	917	8.7%
1	2733	26.0%
2	1502	14.3%
3	1605	15.3%
4	993	9.5%
5	643	6.1%
6	585	5.6%
7	545	5.2%
8	384	3.7%
9	410	3.9%

Value	Count	Frequency (%)
11	54	0.5%
10	125	1.2%
9	410	3.9%
8	384	3.7%
7	545	5.2%
6	585	5.6%
5	643	6.1%
4	993	9.5%
3	1605	15.3%
2	1502	14.3%

following_company_page
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	10.4 KiB

False	7548
True	2948

Common Values
Chart

Value	Count	Frequency (%)
False	7548	71.9%
True	2948	28.1%

montly_avg_comment_on_company_page
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	33
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.35832698

Minimum	11
Maximum	43
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	11
5-th percentile	12
Q1	18
median	23
Q3	28
95-th percentile	37
Maximum	43
Range	32
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	7.394584451
Coefficient of variation (CV)	0.3165716644
Kurtosis	-0.142551385
Mean	23.35832698
Median Absolute Deviation (MAD)	5
Skewness	0.4775176118
Sum	245169
Variance	54.6798792
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
23	620	5.9%
22	574	5.5%
24	552	5.3%
25	548	5.2%
20	527	5.0%
21	519	4.9%
19	500	4.8%
18	494	4.7%
26	476	4.5%
17	439	4.2%
Other values (23)	5247	50.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
11	321	3.1%
12	325	3.1%
13	312	3.0%
14	379	3.6%
15	301	2.9%
16	346	3.3%
17	439	4.2%
18	494	4.7%
19	500	4.8%
20	527	5.0%

Value	Count	Frequency (%)
43	213	2.0%
42	27	0.3%
41	30	0.3%
40	46	0.4%
39	73	0.7%
38	91	0.9%
37	77	0.7%
36	119	1.1%
35	175	1.7%
34	177	1.7%

working_flag
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	10.4 KiB

False	8884
True	1612

Common Values
Chart

Value	Count	Frequency (%)
False	8884	84.6%
True	1612	15.4%

travelling_network_rating
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	82.1 KiB

3.0	3309
4.0	3072
2.0	2157
1.0	1958

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	4.0
3rd row	2.0
4th row	3.0
5th row	4.0

Common Values

Value	Count	Frequency (%)
3.0	3309	31.5%
4.0	3072	29.3%
2.0	2157	20.6%
1.0	1958	18.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	3309	31.5%
4.0	3072	29.3%
2.0	2157	20.6%
1.0	1958	18.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

number_of_adults
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	82.1 KiB

0.0	4497
1.0	4265
2.0	1115
2.5	619

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	4497	42.8%
1.0	4265	40.6%
2.0	1115	10.6%
2.5	619	5.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	4497	42.8%
1.0	4265	40.6%
2.0	1115	10.6%
2.5	619	5.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Daily_Avg_mins_spend_on_traveling_page
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	34
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.67358994

Minimum	0
Maximum	33
Zeros	36
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	82.1 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	8
median	12
Q3	18
95-th percentile	31
Maximum	33
Range	33
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	7.985012874
Coefficient of variation (CV)	0.5839734049
Kurtosis	-0.1288525779
Mean	13.67358994
Median Absolute Deviation (MAD)	5
Skewness	0.715341989
Sum	143518
Variance	63.7604306
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
10	995	9.5%
9	599	5.7%
8	585	5.6%
6	558	5.3%
7	487	4.6%
11	475	4.5%
13	474	4.5%
14	448	4.3%
12	441	4.2%
15	427	4.1%
Other values (24)	5007	47.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	36	0.3%
1	296	2.8%
2	130	1.2%
3	195	1.9%
4	304	2.9%
5	390	3.7%
6	558	5.3%
7	487	4.6%
8	585	5.6%
9	599	5.7%

Value	Count	Frequency (%)
33	369	3.5%
32	95	0.9%
31	69	0.7%
30	65	0.6%
29	127	1.2%
28	128	1.2%
27	107	1.0%
26	126	1.2%
25	130	1.2%
24	156	1.5%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	UserID	Buy_ticket	Yearly_avg_view_on_travel_page	preferred_device	total_likes_on_outstation_checkin_given	yearly_avg_Outstation_checkins	member_in_family	preferred_location_type	Yearly_avg_comment_on_travel_page	total_likes_on_outofstation_checkin_received	week_since_last_outstation_checkin	following_company_page	montly_avg_comment_on_company_page	working_flag	travelling_network_rating	number_of_adults	Daily_Avg_mins_spend_on_traveling_page
0	0	1000001.0	Yes	307.0	Mobile	38570.0	1	2	Financial	94.0	5993.0	8.0	Yes	11.0	No	1.0	0.0	8.0
1	1	1000002.0	No	367.0	Mobile	9765.0	1	1	Financial	61.0	5130.0	1.0	No	23.0	Yes	4.0	1.0	10.0
2	2	1000003.0	Yes	277.0	Mobile	48055.0	1	2	Other	92.0	2090.0	6.0	Yes	15.0	No	2.0	0.0	7.0
3	3	1000004.0	No	247.0	Mobile	48720.0	1	4	Financial	56.0	2909.0	1.0	Yes	11.0	No	3.0	0.0	8.0
4	4	1000005.0	No	202.0	Mobile	20685.0	1	1	Medical	40.0	3468.0	9.0	No	12.0	No	4.0	1.0	6.0
5	5	1000006.0	No	240.0	Mobile	35175.0	1	2	Financial	79.0	3068.0	0.0	No	13.0	No	3.0	0.0	8.0
6	8	1000009.0	No	285.0	Mobile	7560.0	23	3	Financial	44.0	9526.0	0.0	No	21.0	Yes	2.0	0.0	10.0
7	10	1000011.0	No	262.0	Mobile	28315.0	16	3	Medical	84.0	2426.0	0.0	No	13.0	No	3.0	1.0	6.0
8	11	1000012.0	No	217.0	Mobile	5355.0	15	2	Financial	49.0	4193.0	0.0	Yes	12.0	No	4.0	0.0	10.0
9	12	1000013.0	No	232.0	Mobile	23450.0	26	1	Financial	31.0	2911.0	1.0	No	17.0	No	4.0	1.0	5.0

Last rows

	df_index	UserID	Buy_ticket	Yearly_avg_view_on_travel_page	preferred_device	total_likes_on_outstation_checkin_given	yearly_avg_Outstation_checkins	member_in_family	preferred_location_type	Yearly_avg_comment_on_travel_page	total_likes_on_outofstation_checkin_received	week_since_last_outstation_checkin	following_company_page	montly_avg_comment_on_company_page	working_flag	travelling_network_rating	number_of_adults	Daily_Avg_mins_spend_on_traveling_page
10486	11750	1011751.0	No	231.0	Mobile	16423.0	28	4	Historical site	96.0	3845.0	1.0	No	26.0	No	2.0	0.0	12.0
10487	11751	1011752.0	Yes	383.0	Mobile	14399.0	28	3	Other	58.0	10910.0	6.0	Yes	28.0	No	2.0	1.0	23.0
10488	11752	1011753.0	No	302.0	Mobile	25317.0	24	1	Other	79.0	12093.0	0.0	No	24.0	No	1.0	1.0	29.0
10489	11753	1011754.0	No	247.0	Mobile	11418.0	5	3	Historical site	99.0	9983.0	1.0	No	28.0	No	2.0	0.0	16.0
10490	11754	1011755.0	No	210.0	Mobile	40886.0	5	3	Other	53.0	3024.0	2.0	No	32.0	No	4.0	0.0	14.0
10491	11755	1011756.0	No	279.0	Laptop	30987.0	23	2	Historical site	58.0	2616.0	4.0	No	36.0	No	3.0	1.0	23.0
10492	11756	1011757.0	No	305.0	Mobile	21510.0	6	1	Historical site	55.0	10041.0	4.0	No	30.0	No	1.0	1.0	11.0
10493	11757	1011758.0	No	214.0	Mobile	5478.0	4	3	Beach	103.0	6203.0	3.0	Yes	40.0	Yes	2.0	1.0	12.0
10494	11758	1011759.0	No	382.0	Laptop	35851.0	2	3	Historical site	83.0	5444.0	3.0	No	32.0	No	4.0	0.0	20.0
10495	11759	1011760.0	No	270.0	Mobile	22025.0	8	3	Historical site	104.0	4470.0	2.0	No	29.0	No	1.0	0.0	14.0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows